A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease
Abstract Due to the cardioprotective effects of estrogen, premenopausal women have a relatively lower risk of developing coronary artery disease (CAD). However, the incidence of CAD in premenopausal women has been increasing in recent years. Therefore, the aim of this study is to develop a clinical...
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Nature Portfolio
2025-08-01
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| author | Yahui Qiu Qifeng Guo Xuejuan Feng Weiqiang Xiao Shisen Liang Mei Wei |
| author_facet | Yahui Qiu Qifeng Guo Xuejuan Feng Weiqiang Xiao Shisen Liang Mei Wei |
| author_sort | Yahui Qiu |
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| description | Abstract Due to the cardioprotective effects of estrogen, premenopausal women have a relatively lower risk of developing coronary artery disease (CAD). However, the incidence of CAD in premenopausal women has been increasing in recent years. Therefore, the aim of this study is to develop a clinical prediction model to estimate the risk of CAD in premenopausal women. This study included premenopausal women who underwent coronary angiography at the First Hospital of Hebei Medical University from September 2018 to December 2021. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method was used to identify the optimal variables for predicting the risk of CAD in premenopausal women. A nomogram was then constructed using multivariate logistic regression analysis. Finally, the predictive performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUROC), its calibration performance was assessed using calibration curves, and clinical net benefit was evaluated using Decision Curve Analysis (DCA). A total of 222 premenopausal women were ultimately included for analysis, of whom 86 were diagnosed with CAD. Through LASSO and multivariate logistic regression, five predictive variables were finally selected: age, diabetes mellitus (DM), aspartate transaminase (AST), alkaline phosphatase (ALP), and lipoprotein (a) (Lp(a)). These five variables were used to construct a prediction model, which was presented in the form of a nomogram. The calibration curves of the nomogram showed good fit. The area under the receiver operating characteristic curve (AUROC) for the nomogram was 0.819 (95%CI: 0.760–0.878). Additionally, decision curve analysis (DCA) indicated that the nomogram can achieve good net benefit in clinical applications. |
| format | Article |
| id | doaj-art-90d45ac2fcdc42d08066a2d6befcc70c |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
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| series | Scientific Reports |
| spelling | doaj-art-90d45ac2fcdc42d08066a2d6befcc70c2025-08-20T04:03:03ZengNature PortfolioScientific Reports2045-23222025-08-0115111110.1038/s41598-025-14589-6A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery diseaseYahui Qiu0Qifeng Guo1Xuejuan Feng2Weiqiang Xiao3Shisen Liang4Mei Wei5Department of Heart Center, The First Hospital of Hebei Medicical UniversityDepartment of Nephrology, The First Hospital of Hebei Medicical UniversityDepartment of Heart Center, The First Hospital of Hebei Medicical UniversityDepartment of Heart Center, The First Hospital of Hebei Medicical UniversityDepartment of Heart Center, The First Hospital of Hebei Medicical UniversityDepartment of Heart Center, The First Hospital of Hebei Medicical UniversityAbstract Due to the cardioprotective effects of estrogen, premenopausal women have a relatively lower risk of developing coronary artery disease (CAD). However, the incidence of CAD in premenopausal women has been increasing in recent years. Therefore, the aim of this study is to develop a clinical prediction model to estimate the risk of CAD in premenopausal women. This study included premenopausal women who underwent coronary angiography at the First Hospital of Hebei Medical University from September 2018 to December 2021. The Least Absolute Shrinkage and Selection Operator (LASSO) regression method was used to identify the optimal variables for predicting the risk of CAD in premenopausal women. A nomogram was then constructed using multivariate logistic regression analysis. Finally, the predictive performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUROC), its calibration performance was assessed using calibration curves, and clinical net benefit was evaluated using Decision Curve Analysis (DCA). A total of 222 premenopausal women were ultimately included for analysis, of whom 86 were diagnosed with CAD. Through LASSO and multivariate logistic regression, five predictive variables were finally selected: age, diabetes mellitus (DM), aspartate transaminase (AST), alkaline phosphatase (ALP), and lipoprotein (a) (Lp(a)). These five variables were used to construct a prediction model, which was presented in the form of a nomogram. The calibration curves of the nomogram showed good fit. The area under the receiver operating characteristic curve (AUROC) for the nomogram was 0.819 (95%CI: 0.760–0.878). Additionally, decision curve analysis (DCA) indicated that the nomogram can achieve good net benefit in clinical applications.https://doi.org/10.1038/s41598-025-14589-6Premenopausal womenCoronary artery disease (CAD)NomogramPrediction model |
| spellingShingle | Yahui Qiu Qifeng Guo Xuejuan Feng Weiqiang Xiao Shisen Liang Mei Wei A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease Scientific Reports Premenopausal women Coronary artery disease (CAD) Nomogram Prediction model |
| title | A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| title_full | A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| title_fullStr | A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| title_full_unstemmed | A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| title_short | A nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| title_sort | nomogram for predicting the risk of coronary artery disease in premenopausal women with suspected coronary artery disease |
| topic | Premenopausal women Coronary artery disease (CAD) Nomogram Prediction model |
| url | https://doi.org/10.1038/s41598-025-14589-6 |
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